U.S. patent number 10,077,050 [Application Number 15/163,508] was granted by the patent office on 2018-09-18 for automated driving system for evaluating lane cut-out and method of using the same.
This patent grant is currently assigned to GM GLOBAL TECHNOLOGY OPERATIONS LLC. The grantee listed for this patent is GM GLOBAL TECHNOLOGY OPERATIONS LLC. Invention is credited to Kevin P. Conrad, III, Kevin A. O'Dea, III, Akshat Rajvanshi.
United States Patent |
10,077,050 |
Rajvanshi , et al. |
September 18, 2018 |
Automated driving system for evaluating lane cut-out and method of
using the same
Abstract
The methods and system described herein may be used to assist an
automated driving system of a host vehicle. The methods and system
may, in an exemplary embodiment, be used to determine whether a
host vehicle or a target vehicle is cutting out and, accordingly,
control the acceleration and/or other driving features of the host
vehicle. Generally, the methods described herein contain the steps
of determining that a vehicle is cutting out, determining which
vehicle is cutting out, and then controlling the acceleration of
the host vehicle based on the previous determinations. The
determination of which vehicle is cutting out is made based on
readings gathered by the host vehicle from one or more automated
driving sensors. By using target vehicle sensor data in conjunction
with lane marking sensor data, the host vehicle can determine, not
only that a vehicle is cutting out, but which vehicle(s) are
cutting out.
Inventors: |
Rajvanshi; Akshat (Farmington
Hills, MI), O'Dea, III; Kevin A. (Ann Arbor, MI), Conrad,
III; Kevin P. (South Lyon, MI) |
Applicant: |
Name |
City |
State |
Country |
Type |
GM GLOBAL TECHNOLOGY OPERATIONS LLC |
Detroit |
MI |
US |
|
|
Assignee: |
GM GLOBAL TECHNOLOGY OPERATIONS
LLC (Detroit, MI)
|
Family
ID: |
60269418 |
Appl.
No.: |
15/163,508 |
Filed: |
May 24, 2016 |
Prior Publication Data
|
|
|
|
Document
Identifier |
Publication Date |
|
US 20170341647 A1 |
Nov 30, 2017 |
|
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
B60W
30/14 (20130101); B60W 30/09 (20130101); G05D
1/021 (20130101); B60W 30/08 (20130101); B60W
30/10 (20130101); B60W 30/12 (20130101); G05D
1/0088 (20130101); B60W 2554/00 (20200201); B60W
2554/4041 (20200201); B60W 2554/80 (20200201) |
Current International
Class: |
B60W
30/14 (20060101); B60W 30/09 (20120101); B60W
30/10 (20060101); B60W 30/08 (20120101); G05D
1/00 (20060101); B60W 30/12 (20060101); G05D
1/02 (20060101) |
References Cited
[Referenced By]
U.S. Patent Documents
Primary Examiner: Shaawat; Mussa A
Assistant Examiner: Kim; Kyung J
Attorney, Agent or Firm: Reising Ethington, P.C.
Claims
The invention claimed is:
1. A method for use with an automated driving system installed on a
host vehicle, the automated driving system comprises one or more
automated driving sensor(s) and an automated driving control unit,
and the method comprises the steps of: gathering target vehicle
readings and lane marking readings from the one or more automated
driving sensor(s); determining a relative lateral position
(x.sub.lat) of the host vehicle with respect to a leading target
vehicle in the same lane as the host vehicle based, at least in
part, on the target vehicle readings; predicting a lane cutout
maneuver by the host vehicle or the leading target vehicle using
the target vehicle readings, the lane cutout maneuver is a maneuver
where the host vehicle or the leading target vehicle intentionally
initiates or at least partially begins a lane change or lane
departure from a current lane, the lane cutout maneuver prediction
is at least partially based on the relative lateral position
(x.sub.lat) of the host vehicle with respect to the leading target
vehicle; determining whether the lane cutout maneuver is being
performed by the host vehicle, by the leading target vehicle, or by
both the host and the leading target vehicles, the lane cutout
maneuver determination is at least partially based on a lateral
distance between the host vehicle and a lane marking (x.sub.right,
x.sub.left) and the target vehicle readings; and controlling
acceleration of the host vehicle with the automated driving system
during the lane cutout maneuver, wherein the acceleration control
is at least partially based on the lane cutout maneuver prediction
and the lane cutout maneuver determination.
2. The method of claim 1, wherein the gathering step further
comprises gathering the target vehicle readings from one or more
target sensor(s) mounted on the host vehicle.
3. The method of claim 1, wherein the gathering step further
comprises gathering the lane marking readings from one or more lane
marking sensor(s) mounted on the host vehicle, and determining the
lateral distance between the host vehicle and the lane marking
(x.sub.right, x.sub.left) based, at least in part, on the lane
marking readings.
4. The method of claim 3, wherein each of the lane marking
sensor(s) includes a camera that captures images of a road surface
adjacent the host vehicle, and the gathering step further comprises
gathering the images of the adjacent road surface from the camera
and processing the images to obtain the lane marking readings.
5. The method of claim 1, wherein the predicting step further
comprises predicting a beginning of the lane cutout maneuver by the
host vehicle or the leading target vehicle at least partially based
on a change in the relative lateral position (x.sub.lat) of the
host vehicle with respect to the leading target vehicle over a
suitable period of time.
6. The method of claim 1, wherein the determining step further
comprises calculating a relative lateral velocity (v.sub.lat)
between the host vehicle and the leading target vehicle based on a
rate of change in a plurality of relative lateral position values
(x.sub.lat1 . . . x.sub.latx) over a suitable period of time,
deciding the direction of the relative lateral velocity (v.sub.lat)
of the host vehicle, with respect to the leading target vehicle,
based on whether the relative lateral velocity (v.sub.lat) is a
positive or negative value, and determining if the lane cutout
maneuver is being performed by the host vehicle, by the leading
target vehicle, or by both the host and the leading target vehicles
at least partially based on the direction of the relative lateral
velocity (v.sub.lat).
7. The method of claim 1, wherein the determining step further
comprises using the lane marking readings to obtain a lateral
distance between the host vehicle and a lane marking on the left
side of the host vehicle (x.sub.left) and to obtain a lateral
distance between the host vehicle and a lane marking on the right
side of the host vehicle (x.sub.right), comparing the distances
between the host vehicle and the lane markings on the left and
right sides of the host vehicle (x.sub.right, x.sub.left) to decide
which distance is the lesser of the two, and determining if the
lane cutout maneuver is being performed by the host vehicle, by the
leading target vehicle, or by both the host and the leading target
vehicles at least partially based on the lesser of the two
distances (x.sub.right, x.sub.left).
8. The method of claim 1, wherein the determining step further
comprises calculating a rate of change in at least one of a lateral
distance between the host vehicle and a lane marking on the left
side of the host vehicle (x.sub.left) or a lateral distance between
the host vehicle and a lane marking on the right side of the host
vehicle (x.sub.right), deciding if the rate of change in the at
least one lateral distance (x.sub.right, x.sub.left) is decreasing
at a monotonic rate, and determining if the lane cutout maneuver is
being performed by the host vehicle, by the leading target vehicle,
or by both the host and the leading target vehicles at least
partially based on whether the rate of change is decreasing at the
monotonic rate.
9. The method of claim 1, wherein the determining step further
comprises calculating a direction of a relative lateral velocity
(v.sub.lat) of the host vehicle, with respect to the leading target
vehicle, deciding if a lateral distance between the host vehicle
and a lane marking on a left side (x.sub.left) is less than a
lateral distance between the host vehicle and a lane marking on a
right side (x.sub.right), and deciding if the lesser of the two
lateral distances (x.sub.right, x.sub.left) is decreasing at a
monotonic rate.
10. The method of claim 9, wherein when the direction of the
relative lateral velocity (v.sub.lat) of the host vehicle is to the
left, the lateral distance between the host vehicle and the lane
marking on a left side (x.sub.left) is the lesser of the two
lateral distances, and the lateral distance (x.sub.left) is
decreasing at the monotonic rate, then determining the lane cutout
maneuver is being performed by the host vehicle and is to the left;
and wherein when the direction of the relative lateral velocity
(v.sub.lat) of the host vehicle is to the right, the lateral
distance between the host vehicle and the lane marking on a right
side (x.sub.right) is the lesser of the two lateral distances, and
the lateral distance (x.sub.right) is decreasing at the monotonic
rate, then determining the lane cutout maneuver is being performed
by the host vehicle and is to the right.
11. The method of claim 1, wherein the determining step further
comprises calculating a direction of a relative lateral velocity
(v.sub.lat) of the host vehicle, with respect to the leading target
vehicle, deciding if a lateral distance between the leading target
vehicle and a lane marking on a left side (x.sub.left,T) is less
than a lateral distance between the leading target vehicle and a
lane marking on a right side (x.sub.right,T), and deciding if the
lesser of the two lateral distances (x.sub.right,T, x.sub.left,T)
is decreasing at a monotonic rate.
12. The method of claim 11, wherein when the direction of the
relative lateral velocity (v.sub.lat) of the host vehicle is to the
left, the lateral distance between the leading target vehicle and
the lane marking on a right side (x.sub.right,T) is the lesser of
the two lateral distances, and the lateral distance (x.sub.right,T)
is decreasing at the monotonic rate, then determining the lane
cutout maneuver is being performed by the leading target vehicle
and is to the right; and wherein when the direction of the relative
lateral velocity (v.sub.lat) of the host vehicle is to the right,
the lateral distance between the leading target vehicle and the
lane marking on a left side (x.sub.left,T) is the lesser of the two
lateral distances, and the lateral distance (x.sub.left,T) is
decreasing at the monotonic rate, then determining the lane cutout
maneuver is being performed by the leading target vehicle and is to
the left.
13. The method of claim 1, wherein when it is determined that the
lane cutout maneuver is being performed by the host vehicle, then
the controlling step further comprises: determining if traffic in
an adjacent lane is moving faster than traffic in a current lane
and if the adjacent lane is clear; and increasing the acceleration
of the host vehicle with the automated driving system when it is
determined that the adjacent lane is moving faster than traffic in
the current lane and the adjacent lane is clear.
14. The method of claim 13, wherein the controlling step further
comprises determining whether the lane marking between the current
lane and the adjacent lane is a solid line, and providing no
additional acceleration of the host vehicle with the automated
driving system when the lane marking between the current lane and
the adjacent lane is a solid line.
15. The method of claim 1, wherein when it is determined that the
lane cutout maneuver is being performed by the leading target
vehicle, then the controlling step further comprises determining if
traffic in a current lane is clear before increasing the
acceleration of the host vehicle with the automated driving
system.
16. The method of claim 1, wherein the controlling step further
comprises determining that the lane cutout maneuver is being
performed by both the leading target vehicle and the host vehicle
in the same direction, and providing no additional acceleration of
the host vehicle with the automated driving system when the lane
cutout maneuver is being performed by both the leading target
vehicle and the host vehicle in the same direction.
17. The method of claim 1, wherein the controlling step further
comprises determining if a turn signal of the leading target
vehicle is activated in a same direction as the cutout maneuver of
the host vehicle, and providing no additional acceleration of the
host vehicle with the automated driving system when the turn signal
of the leading target vehicle is activated in the same direction as
the cutout maneuver of the host vehicle.
18. The method of claim 1, wherein the controlling step further
comprises controlling acceleration of the host vehicle in an
anticipatory manner so that a torque increase is requested by the
automated driving system before either the host vehicle or the
leading target vehicle completes the cutout maneuver.
19. The method of claim 1, wherein the automated driving system is
part of an adaptive cruise control (ACC) system that automatically
controls a velocity of the host vehicle based, at least in part, on
a desired velocity provided by a driver.
20. A method for use with an automated driving system installed on
a host vehicle, the automated driving system comprises one or more
automated driving sensor(s) and an automated driving control unit,
and the method comprises the steps of: gathering target vehicle
readings and lane marking readings from the one or more automated
driving sensor(s); determining if a lane cutout maneuver is being
performed by the host vehicle, by a leading target vehicle, or by
both the host and the leading target vehicles, the lane cutout
maneuver determination is at least partially based on a lateral
distance between the host vehicle and a lane marking (x.sub.right,
x.sub.left) and at least partially based on the target vehicle
readings; confirming an availability of an adjacent lane when the
lane cutout maneuver is being performed by the host vehicle or
confirming an availability of a current lane when the lane cutout
maneuver is being performed by the leading target vehicle; and
controlling acceleration of the host vehicle with the automated
driving system during the lane cutout maneuver, wherein the
acceleration control is at least partially based on the lane cutout
maneuver determination and the adjacent lane or current lane
availability confirmation.
21. An automated driving system installed in a host vehicle,
comprising: one or more automated driving sensor(s) configured to
gather target vehicle readings and lane marking readings; and an
automated driving control unit configured to: determining a
relative lateral position (x.sub.lat) of the host vehicle with
respect to a leading target vehicle in the same lane as the host
vehicle based, at least in part, on the target vehicle readings;
predict a lane cutout maneuver by the host vehicle or the leading
target vehicle using the target vehicle readings, the lane cutout
maneuver is a maneuver where the host vehicle or the leading target
vehicle intentionally initiates or at least partially begins a lane
change or lane departure from a current lane, wherein the lane
cutout maneuver prediction is at least partially based on the
relative lateral position (x.sub.lat) of the host vehicle with
respect to the leading target vehicle; determine if the lane cutout
maneuver is being performed by at least one of the host vehicle,
the leading target vehicle, or both the host and the leading target
vehicles, wherein the lane cutout maneuver determination is at
least partially based on a lateral distance between the host
vehicle and a lane marking (x.sub.right, x.sub.left) and at least
partially based on the target vehicle readings; and control
acceleration of the host vehicle with the automated driving system
during the lane cutout maneuver, wherein the acceleration control
is at least partially based on the lane cutout maneuver prediction
and the lane cutout maneuver determination.
Description
FIELD
The present invention generally relates to autonomous or
semi-autonomous vehicle systems and, more specifically, to
autonomous or semi-autonomous systems like an adaptive cruise
control system that controls the acceleration of a host
vehicle.
BACKGROUND
Autonomous or semi-autonomous vehicle systems have been developed
to aid vehicle operators in driving a vehicle and/or to perform
automated operation of the vehicle with no operator intervention
needed. These systems generally use vehicle sensors and other
positional tools to control one or more aspects of vehicle
operation. While autonomous vehicle systems are still being
developed, many vehicle systems that are currently available
provide autonomous or semi-autonomous driving features, such as
adaptive cruise control (ACC). ACC systems allow a vehicle operator
to set a desired speed without having to reset and/or adjust such
speed when a slower leading vehicle inhibits the vehicle from
cruising at the set desired speed. However, these systems are not
without their drawbacks.
For example, in current ACC systems, one or more sensors may be
used to track a target vehicle that is in front of the host vehicle
and to determine the relative position of the target vehicle with
respect to the host vehicle. While this relative positional
information may be useful in terms of maintaining a safe following
distance, it may not be enough by itself to determine whether the
host vehicle, target vehicle, or both vehicles are switching lanes
and how to control the host vehicle in response thereto. With
sufficient information to determine which vehicle is switching
lanes or "cutting out", vehicle autonomous or semi-autonomous
systems, such as ACC systems, may be able to operate more
favorably, thereby creating a better passenger and/or operator
experience.
SUMMARY
According to one embodiment, there is provided a method for use
with an automated driving system installed on a host vehicle, the
automated driving system comprises one or more automated driving
sensor(s) and an automated driving control unit, and the method
comprises the steps of: gathering target vehicle readings and lane
marking readings from the one or more automated driving sensor(s);
predicting a lane cutout maneuver by the host vehicle or a leading
target vehicle using the target vehicle readings, the lane cutout
maneuver prediction is at least partially based on a relative
lateral position (x.sub.lat) of the host vehicle with respect to
the leading target vehicle; determining if the lane cutout maneuver
is being performed by the host vehicle, by the leading target
vehicle, or by both the host and the leading target vehicles, the
lane cutout maneuver determination is at least partially based on a
lateral distance between the host vehicle and a lane marking
(x.sub.right, x.sub.left); and controlling acceleration of the host
vehicle with the automated driving system during the lane cutout
maneuver, wherein the acceleration control is at least partially
based on the lane cutout maneuver prediction and the lane cutout
maneuver determination.
According to another embodiment, there is provided a method for use
with an automated driving system installed on a host vehicle, the
automated driving system comprises one or more automated driving
sensor(s) and an automated driving control unit, and the method
comprises the steps of: gathering target vehicle readings and lane
marking readings from the one or more automated driving sensor(s);
determining if a lane cutout maneuver is being performed by the
host vehicle, by a leading target vehicle, or by both the host and
the leading target vehicles, the lane cutout maneuver determination
is at least partially based on a lateral distance between the host
vehicle and a lane marking (x.sub.right, x.sub.left); confirming an
availability of an adjacent lane when the lane cutout maneuver is
being performed by the host vehicle or confirming an availability
of a current lane when the lane cutout maneuver is being performed
by the leading target vehicle; and controlling acceleration of the
host vehicle with the automated driving system during the lane
cutout maneuver, wherein the acceleration control is at least
partially based on the lane cutout maneuver determination and the
adjacent lane or current lane availability confirmation.
According to another embodiment, there is provided an automated
driving system installed in a host vehicle, comprising: one or more
automated driving sensor(s) configured to gather target vehicle
readings and lane marking readings; and an automated driving
control unit configured to: predict a lane cutout maneuver by the
host vehicle or a leading target vehicle using the target vehicle
readings, wherein the lane cutout maneuver prediction is at least
partially based on a relative lateral position (x.sub.lat) of the
host vehicle with respect to the leading target vehicle; determine
if the lane cutout maneuver is being performed by at least one of
the host vehicle, the leading target vehicle, or both the host and
the leading target vehicles, wherein the lane cutout maneuver
determination is at least partially based on a lateral distance
between the host vehicle and a lane marking (x.sub.right,
x.sub.left); and control acceleration of the host vehicle with the
automated driving system during the lane cutout maneuver, wherein
the acceleration control is at least partially based on the lane
cutout maneuver prediction and the lane cutout maneuver
determination.
DRAWINGS
Preferred exemplary embodiments will hereinafter be described in
conjunction with the appended drawings, wherein like designations
denote like elements, and wherein:
FIG. 1 is a schematic view illustrating a host vehicle having an
exemplary automated driving system installed thereon and a target
vehicle ahead of the host vehicle;
FIG. 2A is a schematic view illustrating a scenario of a host
vehicle cutting out from a lane with a first target vehicle into a
lane with a second target vehicle;
FIG. 2B is a schematic view illustrating a scenario of a host
vehicle cutting out from a lane with a first target vehicle into a
lane that is clear;
FIG. 2C is a schematic view illustrating a scenario of a host
vehicle cutting out from a lane with a first target vehicle into an
opposing lane;
FIG. 2D is a schematic view illustrating a scenario of a target
vehicle cutting out from a lane with a host vehicle into a second
lane;
FIG. 3 is a flowchart illustrating an exemplary method for use with
an automated driving system installed on a host vehicle, such as
the system shown in FIG. 1;
FIG. 4 is a flowchart illustrating an exemplary embodiment of a
determining step of the method illustrated in FIG. 3; and
FIG. 5 is a flowchart illustrating an exemplary embodiment of a
controlling step of the method illustrated in FIG. 3.
DESCRIPTION
The methods and system described herein may be used with any number
of autonomous or semi-autonomous vehicle systems, such as an
adaptive cruise control (ACC) system. The methods and system may,
in an exemplary embodiment, be used to determine whether a host
vehicle or a target vehicle is cutting out and, accordingly,
control the acceleration and/or other driving features of the host
vehicle. As used herein, the term "cutout" (or "cut out") means to
initiate or at least partially begin a lane change or lane
departure from the subject vehicle's current lane. Generally, the
methods described herein contain the steps of determining that a
vehicle is cutting out, determining which vehicle is cutting out
(e.g., a target vehicle or the host vehicle), and then controlling
the acceleration of the host vehicle in an anticipatory manner
based on the previous determinations in an effort to somewhat
imitate human driving behavior. The determination of which vehicle
is cutting out is made based on target vehicle sensor data and lane
marking sensor data gathered by the host vehicle from one or more
automated driving sensors. By using the target vehicle sensor data
in conjunction with lane marking sensor data, the host vehicle can
determine, not only that a vehicle is cutting out, but which
vehicle is cutting out and how to react in response thereto.
With reference to FIG. 1, there is shown a general and schematic
view of an exemplary automated driving system 10 that is installed
on a host vehicle 12 and that may be used to improve maneuvering
around target vehicles 14 (only one shown). The term "automated
driving system" is not limited to fully autonomous vehicle systems
and may be used with any suitably autonomous or semi-autonomous
vehicle system (e.g., Levels 0-4 of the National Highway Traffic
Safety Administration's (NHTSA) scale of vehicle automation).
Furthermore, the present system and method may be used with any
type of vehicle, including traditional vehicles, hybrid electric
vehicles (HEVs), extended-range electric vehicles (EREVs), battery
electrical vehicles (BEVs), motorcycles, passenger vehicles, sports
utility vehicles (SUVs), cross-over vehicles, trucks, vans, buses,
recreational vehicles (RVs), etc. These are merely some of the
possible applications, as the system and methods described herein
are not limited to the exemplary embodiments described herein and
illustrated in FIGS. 1-5, and may be implemented in any number of
different ways.
According to one example, automated driving system 10 includes
automated driving sensors, such as vehicle sensors 20-26, target
sensors 30-32, and lane marking sensors 34-36, as well as a control
module 40, one or more braking devices 50-56, and an engine control
module 60. As used herein, an "automated driving sensor" is a
sensor that is capable of gathering information for the automated
driving system that may enable better operation of one or more
autonomous or semi-autonomous feature(s) of the host vehicle. For
example, such information may pertain to the host vehicle, one or
more target vehicle(s), lane markers, other roadway attributes or
conditions, other traffic information, environmental conditions
(e.g., the weather), etc.
Any number of different sensors, devices, modules, and/or systems
may provide automated driving system 10 with information or input
that can be used by the present method. These include, for example,
the exemplary sensors shown in FIG. 1, as well as other sensors
that are known in the art but are not shown here. It should be
appreciated that vehicle sensors 20-26, target sensors 30-32, lane
sensors 34-36, as well as any other sensor utilized by automated
driving system 10 may be embodied in hardware, software, firmware
or some combination thereof. These sensors may directly sense or
measure the conditions or characteristics for which they are
provided, or they may indirectly evaluate such conditions or
characteristics based on information provided by other sensors,
devices, modules, systems, etc.
Furthermore, these automated driving sensors may be electronically
coupled to control module 40 in a number of ways well known in the
art, such as, for example, through one or more wires or cables, a
communications bus, a network, through a wireless connection, etc.
These sensors may be integrated within another vehicle device,
module, system, etc. (e.g., sensors integrated within an engine
control module (ECM), traction control system (TCS), electronic
stability control (ESC) system, antilock brake system (ABS), etc.),
they may be stand-alone components (as schematically shown in FIG.
1), or they may be provided according to some other arrangement. It
is possible for any of the various sensor readings described below
to be provided by some other device, module, system, etc. in host
vehicle 12 instead of being directly provided by an actual sensor
element. In some instances, multiple sensors may be employed to
sense a single parameter (e.g., for providing redundancy, security,
etc.). It should be appreciated that the foregoing scenarios
represent only some of the possibilities, as any type of suitable
sensor arrangement may be used by automated driving system 10, and
therefore, system 10 is not limited to any particular sensor or
sensor arrangement.
Vehicle sensors 20-26 may provide automated driving system 10 with
a variety of host vehicle readings and/or other information that
can be used by the present method. In one embodiment, vehicle
sensors 20-26 generate host vehicle readings that are
representative of the position, velocity, acceleration and/or other
dynamics of host vehicle 12. Some examples of such host vehicle
readings include a host vehicle velocity reading, a host vehicle
acceleration reading, and a host vehicle yaw rate reading. Vehicle
sensors 20-26 may utilize a variety of different sensors and
sensing techniques, including those that use rotational wheel
speed, ground speed, accelerator pedal position, gear shifter
selection, accelerometers, engine speed, engine output, throttle
valve position, and inertial measurement unit (IMU) output, to name
a few. In the example shown in FIG. 1, individual wheel speed
sensors 20-26 are coupled to each of the host vehicle's four wheels
and separately report the rotational velocity of the four wheels.
Skilled artisans will appreciate that these sensors may operate
according to optical, electromagnetic or other technologies, and
that other vehicle readings may be derived or calculated from the
output of these sensors, such as vehicle acceleration. In another
embodiment, vehicle sensors 20-26 determine vehicle speed relative
to the ground by directing radar, laser, and/or other signals
towards the ground and analyzing the reflected signals, or by
employing feedback from a Global Positioning System (GPS). As
mentioned above, vehicle sensors 20-26 may be part of some other
device, module, system, etc., like an anti-lock braking system
(ABS).
Target sensors 30-32 also provide automated driving system 10 with
a variety of target vehicle readings and/or other information that
can be used by the present method. In one example, target sensor 30
generates target vehicle readings that are representative of the
respective position, velocity, and/or acceleration of one or more
target vehicles 14 or other target objects. These readings may be
absolute in nature (e.g., a target vehicle velocity reading or a
target vehicle acceleration reading) or they may be relative in
nature (e.g., a relative velocity reading which is the difference
between target and host vehicle velocities, or a relative
acceleration reading which is the difference between target and
host vehicle accelerations). These target vehicle readings can
pertain to longitudinal readings (e.g., the relative longitudinal
velocity; how fast one vehicle is traveling down the road compared
to the other) or lateral readings (e.g., the relative lateral
velocity; how fast one vehicle is drifting out of a lane compared
to the other). In one example, target sensor 30 may include a
camera that captures images of a target vehicle 14 that is
positioned in front of host vehicle 12. Then, the images may be
processed to obtain distances x.sub.left,T and x.sub.right,T, which
may indicate the distance between the respective side of the target
vehicle and a lane marker, such as lane markers 18.sub.2 and
18.sub.3. Target sensor 30 may be a single sensor or a combination
of sensors, and may include, for example and without limitation, a
light detection and ranging (LIDAR) device, a radio detection and
ranging (RADAR) device, a vision device (e.g., camera, etc.), a
vehicle-to-vehicle communications device, or a combination
thereof.
Lane marking sensors 34-36 gather lane marking readings that can be
provided to automated driving system 10 and used by the present
method. In one embodiment, the lane marking sensors are cameras
that capture images of the road on the sides and/or in front of the
host vehicle wherein lane markers may be located, such as the
dashed lane markers shown at 18.sub.2 and 18.sub.3 or the solid
lane markers shown at 18.sub.1 and 18.sub.4. Then, through
processing the captured images and/or other lane marking readings
using image processing software or firmware, one or more lane
markers may be identified. In a different embodiment, road side
sensors send wireless signals to the host vehicle that can be used
by the present method. Additionally, features, attributes,
readings, measurements, and/or properties may be determined through
evaluation of the images and/or other lane marking readings
collected by the system 10. The processing may be carried out by
processing device 44 in control module 40, by the lane marking
sensors 34-36, or other device capable of processing the images. In
one example, the lane marking readings include the distance between
the left side of host vehicle 12 and a lane marker 18.sub.2,
distance x.sub.left, and may be determined through image processing
of images captured by sensor 34 on the left side of vehicle 12.
Similarly, lane marking sensor 36 may determine the distance
x.sub.right.
In other embodiments, x.sub.left and x.sub.right may be calculated
using different reference points. For x.sub.left, such distance may
be the distance between the midpoint of the host vehicle 12 and the
lane marker 18.sub.2, the distance between the left side of the
host vehicle 12 and another lane marker located to the left of the
host vehicle (e.g., lane marker 18.sub.1). Similarly, the same is
true for x.sub.right with respect to the right side as opposed to
the left side. Furthermore, other distances may be calculated using
the lane marking sensors 34-36, such as those distances between a
reference point on a target vehicle and a lane marker (e.g.,
x.sub.left and x.sub.right where, instead of the distance relating
to the host vehicle, it relates to a target vehicle). It should be
appreciated that x.sub.left,T and x.sub.right,T may be calculated
in a like manner, however, with respect to the target vehicle as
opposed to the host vehicle.
In addition to the above, in various embodiments, a camera or other
vision device could be used in conjunction with one or more of
sensors 30-36. For instance, a forward viewing camera could be
located towards the center of the windshield and arranged to detect
lane markings in the current lane 16.sub.2, in one or more adjacent
lanes 16.sub.1, 16.sub.3, or some combination thereof. Accordingly,
automated driving system 10 is not limited to any particular type
of sensor or sensor arrangement, specific technique for gathering
or processing sensor readings, or particular method for providing
sensor readings, as the embodiments described herein are simply
meant to be exemplary. Vehicle sensors 20-26, target sensors 30-32,
and lane marking sensors 34-36 are all examples of automated
driving sensors.
Control module 40 may be, in one embodiment, an automated driving
control unit. Control module 40 may include any variety of
electronic processing devices, memory devices, input/output (I/O)
devices, and/or other known components, and may perform various
control and/or communication related functions. In an exemplary
embodiment, control module 40 includes an electronic memory device
42 that stores various sensor data (e.g., vehicle sensor data,
target vehicle sensor data, and lane marking sensor data from
automated driving sensors 20-26, 30-32, and 34-36), look up tables
or other data structures, algorithms (e.g., those that may be
utilized in the method described below), various threshold values,
etc. Memory device 42 may also store pertinent characteristics and
background information pertaining to vehicle 12, such as
information relating to stopping distances, deceleration limits,
maximum braking capability, turning radius, temperature limits,
moisture or precipitation limits, driving habits or other driver
behavioral data, etc. Control module 40 may also include an
electronic processing device 44 (e.g., a microprocessor, a
microcontroller, an application specific integrated circuit (ASIC),
etc.) that executes instructions for software, firmware, programs,
algorithms, scripts, etc., that are stored in memory device 42 and
may govern and perform the processes and methods described herein.
Control module 40 may be electronically connected to other vehicle
devices, modules and systems via suitable vehicle communications
and can interact with them when required. These are, of course,
only some of the possible arrangements, functions and capabilities
of control module 40, as other embodiments could also be used.
Depending on the particular embodiment, control module 40 may be a
stand-alone vehicle electronic module (e.g., an object detection
controller, a safety controller, etc.), it may be incorporated or
included within another vehicle electronic module (e.g., an
integrated controller within the unit that includes the target
sensors, a park assist control module, electronic brake control
module (EBCM), etc.), or it may be part of a larger network or
system (e.g., an active safety system, a traction control system
(TCS), electronic stability control (ESC) system, antilock brake
system (ABS), driver assistance system, adaptive cruise control
(ACC) system, lane departure warning system, etc.), to name a few
possibilities. Accordingly, control module 40 is not limited to any
one particular embodiment or arrangement.
Braking devices 50-56 may be a part of any suitable vehicle brake
system, including systems associated with disc brakes, drum brakes,
electro-hydraulic braking, electro-mechanical braking, regenerative
braking, brake-by-wire, etc. In an exemplary embodiment, braking
devices 50-56 are disc brakes and each generally includes a rotor,
a caliper, a piston, and brake pads (not shown) and may be part of
an electro-hydraulic braking (EHB) system. As is appreciated by
skilled artisans, a tire-wheel assembly (not shown) is attached to
a hub with several lug nuts so that the tire, wheel, hub, and rotor
can all co-rotate together. A brake caliper straddles the rotor and
carries a brake piston so that a compressive and frictional brake
force can be applied by brake pads to opposing sides of the rotor
during a braking event. The frictional brake forces slow the
rotation of the rotor and hence the rotation of the tire-wheel
assembly and ultimately the vehicle. The brake pistons for each of
the different wheels or corners may be: all controlled in unison,
controlled on a wheel-by-wheel basis, controlled in groups (e.g.,
the front wheels are controlled separately from the rear wheels),
or controlled according to some other known method. Again, it
should be appreciated that the preceding description of braking
devices 50-56 is only provided for purposes of illustration. The
methods described herein may be used with any number of different
braking devices including those found in electro-mechanical braking
systems (EMB) or other brake-by-wire systems. For instance, braking
devices 50-56 could be substituted with other suitable components,
such as electro-mechanical brakes having electric calipers
(e-calipers), drum brakes, and hybrid vehicle brakes that use
regenerative braking.
Engine control module (ECM) 60 is preferably designed to govern one
or more aspects of vehicle propulsion by controlling an internal
combustion engine, an electric motor, a combination thereof, or
other vehicle propulsion mechanism. In an exemplary embodiment, the
control module 40 is connected via a communications bus to ECM 60.
Control module 40 may then direct ECM 60 to increase, decrease, or
maintain the propulsion of the internal combustion engine of
vehicle 12. In addition, or in another embodiment, ECM 60 may be
connected to braking devices 50-56 and may operate in conjunction
therewith.
Turning now to FIGS. 2A-2D, there are shown several different
potential scenarios that a host vehicle 12 may encounter while
driving with the assistance of automated driving system 10. In
these scenarios and in the corresponding description, it is assumed
that system 10 is an adaptive cruise control (ACC) system and that
the host vehicle 12 is following a slower moving leading target
vehicle 14 before a cut-out event starts to occur. The figures each
show at least one target vehicle 14 that is in front of the host
vehicle 12. The arrows indicate where the vehicle (host vehicle in
FIGS. 2A-2C and target vehicle 14.sub.1 in FIG. 2D) is heading
and/or intending to head (i.e., the direction of a cut-out
maneuver). FIGS. 2A-2D will be used in conjunction with FIG. 1 to
facilitate the description of the exemplary embodiments presented
below by providing an illustrative reference to some scenarios in
which the methods, shown in FIGS. 3-5, may be used. It should be
appreciated that the scenarios depicted in FIGS. 2A-2D are
non-limiting and are only a few of the large number of possible
scenarios a host vehicle may encounter.
Turning now to FIG. 3, there is shown an exemplary method 200 for
use with an automated driving system 10 installed on a host vehicle
12. The automated driving system comprises one or more automated
driving sensor(s) and an automated driving control unit, such as
those previously described. Although the description below is
primarily discussed with reference to a leading target vehicle
14.sub.1, it should be appreciated that the discussion below is
non-limiting and applicable to trailing and/or nearby/adjacent
target vehicles as well.
The method 200 begins with step 210 wherein the automated driving
system 10 on the host vehicle 12 gathers target vehicle readings
from one or more automated driving sensor(s). In one embodiment,
the target sensors 30-32 may gather information relating to a
relative lateral position between host vehicle 12 and target
vehicle 14.sub.1 (x.sub.lat). Additionally, or alternatively, the
control module 40 may receive host vehicle readings from the
vehicle sensors 20-26 that are representative of, or that
correspond to, values of certain conditions/parameters, such as, a
host vehicle velocity, a relative velocity with respect to a target
vehicle, a relative distance with respect to a target vehicle, an
actual target vehicle velocity, and/or an identification of a lane
in which a target vehicle 14 or the host vehicle 12 is located.
These readings and/or signals may then be stored in memory, such as
electronic memory device 42 in control module 40.
In step 220, the automated driving system 10 gathers lane marking
readings from one or more automated driving sensor(s). For example,
the lane marking sensors 34-36 may be used to gather or capture
information relating to one or more lane markers, such as distances
x.sub.left and x.sub.right. The distances x.sub.left and
x.sub.right may be calculated as the distance between the host
vehicle and the lane marking on the respective side of the host
vehicle's current lane (e.g., x.sub.left being the distance between
the left most side of host vehicle 12 and a lane marking of lane
18.sub.2 and x.sub.right being the distance between the right most
side of host vehicle 12 and a lane marking of lane 18.sub.3).
Alternatively, the distances x.sub.left and x.sub.right may be the
distance between another lane on the respective side and the host
vehicle (e.g., x.sub.left being the distance between the left most
side of host vehicle 12 and a lane marking of lane 18.sub.1 and
x.sub.right being the distance between the right most side of host
vehicle 12 and a lane marking of lane 18.sub.4). In other
embodiments, the distances may be the distance between the center
of host vehicle 12 and one or more lane markings of a lane. Other
embodiments include any distance between one or more lane markings
of a lane and one or more reference points of host vehicle 12
and/or target vehicle(s) 14.
In one embodiment, the lane marking sensors 34-36 may be cameras
that capture images of the road surface adjacent to the host
vehicle. The captured images may then be processed by the sensors
34-36 and/or processed by processing device 44 of control module 40
to determine information pertaining to one or more lane markers 18,
such as distances x.sub.left and/or x.sub.right. The results of the
image processing may be used with other information, such as that
information gathered in step 210 to make further determinations
regarding the lane markers, such as to determine the distances
x.sub.left and x.sub.right and/or whether the target vehicle(s) are
in the same lane as host vehicle 12 or in an adjacent lane to host
vehicle 12.
In another embodiment, the sensors 34-36 and/or target vehicle
sensors 30-32 may be cameras that capture images of one or more
target vehicle(s) 14 and/or the road near the target vehicle(s).
This information may then be processed by sensors 30-36 themselves
or by processing device 44 to determine lane marking information
pertaining to the one or more target vehicle(s), such as distances
x.sub.left and/or x.sub.right that correspond to the target
vehicle(s) and one or more lane markers 18. Additionally, other
information may be obtained from this lane marking sensor data,
such as the identity of the lane in which the target vehicle(s) are
in or whether the target vehicle(s) are in the same lane as the
host vehicle. In any event, it should be appreciated that steps 210
and 220 may be carried out in any order and/or in a concurrent
fashion and that the order presented by FIG. 2 is merely
exemplary.
In step 230, the automated driving system 10 predicts a lane cutout
maneuver by the host vehicle or a leading target vehicle using the
target vehicle readings. The lane cutout maneuver determination is
at least partially based on a relative lateral position or distance
of the host vehicle with respect to the leading target vehicle
(x.sub.lat). In one embodiment, the relative lateral position
(x.sub.lat) is obtained in step 210 by evaluating the target
vehicle readings and/or host vehicle readings that may be gathered
by sensors 20-32. For example, if the relative lateral position
(x.sub.lat) between the host vehicle and the leading target vehicle
14.sub.1 is more than a threshold amount, the automated driving
system 10 may predict that a cutout maneuver by either the target
vehicle 14.sub.1 or the host vehicle 12 is taking place. In
addition, a change in relative lateral position (x.sub.lat) over
time may be calculated by taking multiple readings and/or sensor
data from the sensors 20-26 and/or 30-32. This change in relative
lateral position (x.sub.lat) over time may be used to make a more
accurate prediction, as it mitigates false positives that may occur
from merely using one relative lateral distance. This may
particularly be useful in the case where the host vehicle 12 and
target vehicle 14.sub.1 are drifting in the same lane. Other
techniques for predicting a lane cutout maneuver based at least
partially on relative lateral position x.sub.lat may be used,
including using relative lateral velocity v.sub.lat or other
parameters derived from x.sub.lat. Of course, yaw rate, steering
wheel angle, and other vehicle parameters may also be used in this
lane cutout prediction. After it is determined that a cutout
maneuver is being performed, step 240 is carried out.
In step 240, the automated driving system 10 determines if the lane
cutout maneuver is being performed by the host vehicle or by the
leading target vehicle. In other embodiments, the automated driving
system may determine whether a lane cutout maneuver is being
performed by a trailing target vehicle or a nearby/adjacent target
vehicle. In any event, the lane cutout maneuver determination may
be at least partially based on the lateral distance between the
host vehicle and a lane marking (x.sub.left, x.sub.right).
Referring now to FIG. 4, there is provided a more detailed
flowchart of an exemplary embodiment of a determining step 240 of
the method illustrated in FIG. 3. The exemplary embodiment of step
240 illustrates steps 241-248, and begins with step 241 wherein it
is determined if the relative lateral velocity (v.sub.lat) is to
the right, to the left, or neither. This determination may be based
on the signals gathered in steps 210 and/or 220, as well as any
other calculations that may be or were derived therefrom, such as
the relative lateral position (x.sub.lat) of the host vehicle with
respect to a target vehicle.
In one scenario wherein the host vehicle is cutting out to the left
in an attempt to perform a lane change to the left, such as is
shown in FIGS. 2A and 2B, the relative lateral velocity (v.sub.lat)
of the leading target vehicle is to the right, from the perspective
of the host vehicle (i.e., when the host vehicle moves left, the
target vehicle becomes located on the right side of the host
vehicle, as is seen in FIG. 1). However, in the case where the
target vehicle is cutting out to the right, the relative lateral
velocity (v.sub.lat) of the target vehicle would be to the right as
well and, thus, the directionality of v.sub.lat is not, by itself,
enough to determine which vehicle is cutting out. The same problem
arises in determining whether the target vehicle is cutting to the
left or whether the host vehicle is cutting to the right.
Therefore, more information is needed to determine which vehicle is
performing the cutout. Such information could be distances and/or
rates of change of distances between the host vehicle and one or
more lane markers on the roadway nearby or adjacent to the host or
target vehicle.
In one embodiment of step 241, the host vehicle may use processing
device 44 of control module 40 to determine a relative lateral
velocity (v.sub.lat) of a target vehicle 14.sub.1. Generally
speaking, the relative lateral velocity equals the rate of change
of the relative lateral position as a function of time
(v.sub.lat=.DELTA.x.sub.lat/.DELTA.t). For example, the vehicle may
use target vehicle readings, as collected in step 210, to calculate
a plurality of relative lateral positions (x.sub.lat,1,
x.sub.lat,2, . . . x.sub.lat,n) of the host vehicle 12 with respect
to target vehicle 14.sub.1. The method may gather these readings
and associate a timestamp with each corresponding x.sub.lat value.
Then, with a plurality of x.sub.lat and timestamp pairs, the method
may calculate the rate of change of the relative lateral position
between the host vehicle and target vehicle by calculating the
change in position as a function of time. This yields a relative
lateral velocity that may be positive or negative depending on the
lateral direction in which the target vehicle is moving with
respect to the host vehicle (e.g., a positive x.sub.lat value
indicates the target vehicle is to the right of the host vehicle,
as shown in FIG. 1). To illustrate, if both vehicles are moving
either right or left at the same rate (e.g., if both vehicles are
cutting out), then the relative lateral velocity would equal zero.
After calculation of one or more relative lateral velocities, the
method may determine if the relative lateral velocity (v.sub.lat)
is to the right, to the left, or not to either side. In the latter
case, this may be due to the fact that neither the host vehicle nor
the target vehicle is cutting out, or may be due to the fact that
both the host vehicle and the target vehicle are cutting out.
In step 242, the distance between the host vehicle and the left
lane marker (x.sub.left) is compared to the distance between the
host vehicle and the right lane marker (x.sub.right). As mentioned
previously, this information can be used to aid the vehicle in
determining whether the host vehicle is cutting out or whether the
target vehicle is cutting out. For instance, the host vehicle
cutting out to the left and the target vehicle cutting out to the
left may (and most likely will) evaluate to the same result in step
241, thus, additional criteria is needed to identify which vehicle
is starting to change lanes.
In one embodiment of step 242, the distances x.sub.left and
x.sub.right are obtained from lane marking sensors 34 and 36,
respectively, and are the distances between some reference point on
the host vehicle 12 and the nearest lane marker on the respective
side of the host vehicle, as shown in FIG. 1. After these distances
are obtained, as may be the case in step 220, then the two
distances are compared to one another. The distances may be
compared by the processing device 44 in control module 40. In
another embodiment, step 242 uses the direction of relative lateral
velocity (from the previous step) to determine which side (left or
right) to evaluate.
In step 243, it is determined whether the lesser of the two
distances (x.sub.left or x.sub.right as determined in step 242) is
decreasing at a monotonic rate and in the opposite direction of
v.sub.lat. As used herein, "monotonic rate" broadly means any rate
that, when evaluated over a suitable period of time, is
substantially increasing or decreasing, but not both. A suitable
period of time may be the time it takes to begin or initiate a
cutout maneuver. In a first scenario as shown in FIG. 2A, host
vehicle 12 is following a slower target vehicle 14, and is cutting
out to the left lane and, therefore, the distance x.sub.left is
most likely less than the distance x.sub.right. Further, the
distance x.sub.left will be decreasing as the host vehicle 12
progresses into the left lane and in the opposite direction of
v.sub.lat, which would be to the right in this case. A plurality of
distances x.sub.left may be calculated from information gathered in
step 220. The vehicle may then compare the distances with one
another to see whether the distances are decreasing at a monotonic
rate and in the opposite direction of v.sub.lat. If the distance
x.sub.left was decreasing, but not in the opposite direction of
v.sub.lat (e.g., the same direction of v.sub.lat), then this may
indicate that the target vehicle is performing a lane change, as
will be illustrated in steps 245 to 248. If the lesser distance is
decreasing at a monotonic rate and in the opposite direction of
v.sub.lat, the method continues to step 244; otherwise, the method
continues to step 245.
Upon reaching step 244, the method determines that the host vehicle
is cutting out and most likely is changing lanes. The information
used in these determinations may be gathered from some combination
of sensors 20-36 (see steps 210 and 220) and the results of these
determinations may be stored in memory device 42 of control module
40 or other memory device, along with other information pertaining
to this determination and/or values, readings, or calculations.
This information can then be used by the host vehicle 12 to
determine an acceleration profile which the host vehicle may then
operate according to.
In step 245, the vehicle determines whether x.sub.left,T or
x.sub.right,T is the lesser of the two. This step is analogous to
step 242 and may be carried out in a like manner. However, the two
distances, x.sub.left,T and x.sub.right,T are calculated with
respect to the target vehicle 14.sub.1. For example, sensor 30 may
include a camera that may capture images in front of the vehicle
12, which may then be used to determine the distances between the
target vehicle 14.sub.1 and lane markers--e.g., x.sub.left,T is the
distance between the left side of target vehicle 14.sub.1 and lane
marker 18.sub.2 and x.sub.right,T is the distance between the right
side of target vehicle 14.sub.1 and lane marker 18.sub.3. After the
lesser of the two distances are determined (e.g., in FIG. 1,
x.sub.right,T is less than x.sub.left,T), the method continues to
step 246.
In step 246, it is determined whether the lesser of the two
distances (x.sub.left or x.sub.right as determined in step 242) is
decreasing at a monotonic rate and in the same direction of
v.sub.lat. This step is analogous to step 243 and, thus, may be
executed in a like manner. However, this step involves the target
vehicle 14.sub.1's position with respect to the lane markers. For
example, since, as shown in FIG. 1, x.sub.right,T is the lesser of
the two distances, this step will determine if the distance
x.sub.right,T is decreasing at a monotonic rate and in the same
direction as v.sub.lat. Here, if x.sub.right,T is decreasing at a
monotonic rate and in the same direction as v.sub.lat, then it the
target vehicle is most likely cutting out to the right. If the
lesser distance is decreasing at a monotonic rate and in the
opposite direction of v.sub.lat, the method continues to step 247;
otherwise, the method continues to step 248.
Upon reaching step 247, it has been determined that the target
vehicle is cutting out to the side which the relative lateral
velocity (v.sub.lat) is directed, as determined in step 241. For
example, if it is determined that the relative velocity (v.sub.lat)
of the target vehicle is to the right and x.sub.right,T is
decreasing at a monotonic rate, then the target vehicle is cutting
out to the right and most likely making a lane change to the right.
Similarly, this information may be stored in memory device 42 of
control module 40 or other memory device, along with other
information. The method then continues with step 250. Other methods
of confirming a cutout by the leading target vehicle 14 may be
used, such as by confirming that the target vehicle 14 is no longer
in front of the host vehicle 12 with target vehicle sensor 30.
Upon reaching step 248, it has been determined that neither the
target vehicle nor the host vehicle is cutting out. However, it may
be the case that both the host vehicle and the target vehicle are
cutting out in the same direction. If the direction of the relative
lateral velocity (v.sub.lat) is neither to the right nor the left,
but the lesser of the two distances is decreasing at a monotonic
rate, then both the host vehicle and the target vehicle are cutting
out and most likely changing lanes. The vehicle(s), in these cases,
will be making a cutout to the side to which the distance is
decreasing. For example, if x.sub.left is less than x.sub.right and
the other conditions are satisfied, then the host vehicle is
probably making a left lane change, such as is seen in FIGS. 2A and
2B. However, if neither distance is decreasing at a monotonic rate
for a sufficient amount of time, then neither vehicle is likely
performing a cutout.
In steps 244, 247, and/or 248, the determination of whether the
host vehicle or target vehicle is cutting out may be corroborated
by other indications obtained by the host vehicle. For example, the
host vehicle may determine that a host vehicle operator turned on
the vehicle 12's turn signal. Also, the host vehicle may realize
that a host vehicle operator is turning the steering wheel thereby
providing further information to corroborate the determinations in
steps 244, 247, and/or 248. Additionally, through use of sensor 30,
which may be a camera, or a vehicle-to-vehicle (V2V) system, the
host vehicle 12 may obtain information indicating that the target
vehicle 14.sub.1 is cutting out towards a certain direction, such
as the activation of turn signals or other information regarding
target vehicle 14.sub.1. Any other useful information that may be
obtained by sensors 20-36 may be used by host vehicle 12 to
corroborate the determinations in step 240 as well, such as traffic
or positioning information obtained at vehicle modules and/or via
V2V communications.
Referring back now to FIG. 3, in step 250, when the cutout maneuver
is being performed by the host vehicle, the method confirms the
availability of an adjacent lane before accelerating the host
vehicle. The adjacent lane confirmation is at least partially based
on a presence or absence of an additional target vehicle in the
adjacent lane. For example, in FIG. 2A, the target vehicle 14.sub.2
is in an adjacent lane, namely the adjacent lane to which host
vehicle 12 seeks to cut out towards. In this instance, information
may be gathered upon reaching this step, in step 210 and/or in step
220 that pertains to the presence or absence of an additional
target vehicle or other object (e.g., a traffic cone).
For example, referring back to step 210, not only may the target
vehicle sensors 30-32 be used to confirm that a target vehicle
14.sub.1 is leading host vehicle 12, but the target vehicle sensors
may detect an additional vehicle 14.sub.2 in an adjacent lane, such
as is the case in FIG. 2A. In another example, in step 220, the
lane marking sensors 34-36 may include cameras that are capable of
capturing images of the adjacent lanes wherein a target vehicle
14.sub.2 is located and, through image processing, may determine
that the image shows a target vehicle or object in an adjacent
lane. In a third example, the host vehicle 12, upon reaching step
250, may operate target vehicle sensors 30-32 to get updated
readings of the adjacent lane and additional target vehicle
14.sub.2. This last example may be preferable in some instances
when, for instance, the vehicle is part-way through its cutout
maneuver and, therefore, has a clearer path of detection in the
adjacent lane to which it is cutting out towards. In this case,
vehicle 14.sub.1 may not be as obtrusive to the target vehicle
sensors with respect to detecting a second target vehicle 14.sub.2.
Furthermore, the host vehicle may determine whether this additional
target vehicle 14.sub.2 is in the adjacent lane to which the host
vehicle is cutting out towards (see step 244). These steps may be
carried out by processing device 44 of control module 40 and/or by
the one or more sensors 20-26 and/or 30-36 included in the vehicle.
The method then continues to step 260.
In step 260, the automated driving system controls the acceleration
of the host vehicle during the lane cutout maneuver. The
acceleration control is at least partially based on the lane cutout
maneuver prediction (step 230), the lane cutout maneuver
determination (step 240), and/or the adjacent lane confirmation
(step 250). Additionally, the acceleration control may also be
carried out based on other information regarding the host vehicle
12, one or more target vehicles 14 (e.g., the presence of, and/or
any other information pertaining to, a leading vehicle, a trailing
vehicle, an adjacently located vehicle), environmental factors
(e.g., weather, potential road conditions due to the weather),
roadway factors (e.g., slope, pitch, and/or curve of the roadway;
number of lanes; dashed versus solid lane markings; speed limit of
the roadway), or any other information that may be used to
determine an appropriate acceleration control of the host vehicle
12.
Referring now to FIG. 5, there is provided a flowchart illustrating
an exemplary embodiment of a controlling step 260 of the method
200. The exemplary embodiment of step 260 contains steps 261-265
and is carried out after step 250. As mentioned previously, the
present method may be used with any number of autonomous or
semi-autonomous vehicle systems, but is particularly well suited
for adaptive cruise control (ACC) systems. Thus, the following
description is directed to an example of step 260 where an ACC
system automatically controls acceleration, while a driver controls
steering. Therefore, the following example does not address issues
like whether or not a certain lane change should be made, as it is
assumed the driver is in control of steering. Such features could,
however, be added to the present system and method. In step 261,
the method decides whether the host vehicle 12 is cutting out or
whether the leading target vehicle is cutting out. This
determination was already made in step 240 and, therefore, this
step 261 may merely include recalling from memory this information.
Upon the determination that the host vehicle 12 is cutting out, the
method continues to step 262; otherwise, the method continues to
step 264.
In step 262, the automated driving system 10 determines whether the
adjacent lane towards which the host vehicle 12 is cutting out is
moving faster, and/or is clear. As used herein, when referring to
whether a lane is "moving faster", this means that the lane which
is "moving faster" contains traffic (e.g., target vehicles) that is
traveling down the road at a faster speed relative to the host
vehicle 12, than the traffic in the host vehicle's current lane.
For example, in FIG. 2A, if vehicle 14.sub.2 is travelling faster
than vehicle 14.sub.1 with respect to host vehicle 12, then it
could be said that the left lane is "moving faster" than the center
lane. Similarly, if vehicle 14.sub.2 was in the left lane but was
trailing vehicle 12, the left-most lane may still be regarded as
"moving faster" because trailing vehicle 14.sub.2 is travelling at
a higher speed than vehicle 12, even though the left lane may not
be clear.
As used herein, a lane is "clear" if there is no vehicle in the
lane that is leading host vehicle 12 by some distance. For example,
in FIG. 2B, the host vehicle is shown as intending to cut out to
the left lane. There is no vehicle located in the left lane that is
leading vehicle 12 and, therefore, it can be said that the left
lane is clear, at least with respect to vehicle 12. In FIG. 2A, the
host vehicle 12 is seeking to cut out to the left lane, however, a
target vehicle 14.sub.2 is located in the left lane and is leading
vehicle 12. Therefore, this left lane is not "clear" at least with
respect to vehicle 12. Also, if, as determined in step 240, the
leading target vehicle and the host vehicle are both cutting out,
then the lane is most likely not clear. In other embodiments,
although a lane contains another vehicle, if that vehicle is not
within a predetermined or certain distance to host vehicle 12
(i.e., very far ahead of the host vehicle), it may still be said
that the lane is clear. In yet another embodiment, a lane to which
the host vehicle is cutting out towards may be said to not be
clear, even though there is no leading target vehicle in the lane,
if there is a target vehicle in the lane that is approaching from
behind, as determined by target vehicle sensor 32, for example. It
should be appreciated that any number of known techniques for
performing step 262 may be used.
In one embodiment of step 262, the automated driving system 10 may
use information already gathered and/or stored in memory, such as
electronic memory device 42 or control module 40. In other
embodiments, the vehicle may, upon reaching this step, gather
information via one or more sensors 20-26 and/or 30-36. In any
event, the control module may use information pertaining to the
host vehicle 12 and one or more target vehicles 14 to determine
whether the adjacent lane to which the host vehicle is cutting out
towards is clear and/or moving faster. If the adjacent lane is
clear and/or moving faster, then the method continues to step 265;
otherwise, the method continues to step 263.
In step 264, which is encountered when the leading target vehicle
is cutting out or switching lanes (e.g., FIG. 2D), the method
determines whether the host vehicle's current lane is clear. This
determination may be made in a manner similar to the
determination(s) made in step 262. For example, the target vehicle
readings gathered in step 210 may be recalled from memory and then
used to determine if there is a vehicle ahead of the target vehicle
14.sub.1. In another example, the method may use target vehicle
sensor 30 to determine if there is a vehicle ahead of the host
vehicle 12 in the current lane after the target vehicle 14.sub.1
completes its cutout to another lane. If the lane is clear, the
method proceeds to step 265; otherwise, the method ends. In an
alternate embodiment, other factors may be taken into consideration
to determine whether the automated driving system should provide
negative acceleration or positive acceleration to the host
vehicle.
Upon reaching step 263, a negative acceleration is provided to the
host vehicle. This step is encountered when the host vehicle is
cutting out to another lane wherein traffic is moving slower than
vehicle 12 and/or wherein the new lane is not clear. This scenario
may be visualized through viewing FIG. 2A, assuming that vehicle 12
is moving faster than vehicle 14.sub.2. In this case, it is
desirable to slow the velocity of host vehicle 12 via application
of negative acceleration or negative torque. The processing device
44 in control module 40 may make this determination and,
subsequently, may generate and/or send control signals to braking
devices 50-56 and/or ECM 60. Depending on certain readings,
measurements, or other information, the automated driving system 10
may determine the extent to which the vehicle's velocity must be
slowed such that it does not contact another object (e.g., a target
vehicle 14) and/or such that the transition between lanes is smooth
or comfortable for the passenger(s). Such information that may be
taken into account during this determination or generation of
control signals are the speeds of vehicle 12 and target vehicles
14, the distance(s) between host vehicle 12 and target vehicle(s)
14, the speed limit of the roadway, the nature of the lane (e.g.,
whether it is the left-most lane (e.g., the fast lane), the
right-most lane (e.g., the deceleration lane)), etc. Other
information that can be useful may be roadway-related or other
vehicle information obtained from an infotainment module, the
control module 40, a telematics unit, a global positioning system
(GPS), etc. It should be appreciated that there are numerous other
scenarios wherein the automated driving system 10 may determine
that host vehicle 12 should be provided with a negative
acceleration. The method then ends.
Upon reaching step 265, a positive acceleration is provided to the
host vehicle. This step is analogous to step 263, except that a
positive acceleration is provided to the host vehicle. This step
may be carried out, for example, when: (1) the host vehicle cuts
out to a lane that is moving faster (see FIG. 2A wherein it target
vehicle 14.sub.2 is traversing the road at a higher speed than host
vehicle 12); (2) the host vehicle cuts to a lane that is clear (see
FIG. 2B); or (3) a leading target vehicle 14.sub.1 cuts out to
another lane, leaving host vehicle 12 with in a clear lane (see
FIG. 2D). However, if it is determined that the lane marker between
the host vehicle's current lane and the adjacent lane towards which
the vehicle 12 is cutting out to is a solid line (e.g., as is the
case shown in FIG. 2C), then no additional torque is provided. It
should be appreciated that there are numerous other scenarios
wherein the automated driving system 10 may determine that host
vehicle 12 should be provided with a positive acceleration. The
method then ends.
Steps 263 and/or 265 may employ any number of techniques and
methods from known autonomous or semi-autonomous driving systems to
help carry out the deceleration and/or acceleration actions
described above. As an example, if the host vehicle is cutting out
towards a solid lane marking (i.e., no passing allowed), then the
method may not provide additional acceleration without consulting
other sensor readings. As another example, if the host vehicle
begins cutting out to the left and the leading target vehicle
14.sub.1 has its left turn signal on, this may also cause the
method to avoid additional acceleration so that the two vehicles do
not collide. Various acceleration profiles could be used based on
factors such as which vehicle is cutting out, whether the host
vehicle is overtaking another vehicle, whether the host vehicle is
crossing a solid line, etc.
It is to be understood that the foregoing description is not a
definition of the invention, but is a description of one or more
preferred exemplary embodiments of the invention. The invention is
not limited to the particular embodiment(s) disclosed herein, but
rather is defined solely by the claims below. Furthermore, the
statements contained in the foregoing description relate to
particular embodiments and are not to be construed as limitations
on the scope of the invention or on the definition of terms used in
the claims, except where a term or phrase is expressly defined
above. Various other embodiments and various changes and
modifications to the disclosed embodiment(s) will become apparent
to those skilled in the art. For example, the specific combination
and order of steps is just one possibility, as the present method
may include a combination of steps that has fewer, greater or
different steps than that shown here. All such other embodiments,
changes, and modifications are intended to come within the scope of
the appended claims.
As used in this specification and claims, the terms "for example,"
"e.g.," "for instance," "such as," and "like," and the verbs
"comprising," "having," "including," and their other verb forms,
when used in conjunction with a listing of one or more components
or other items, are each to be construed as open-ended, meaning
that that the listing is not to be considered as excluding other,
additional components or items. Other terms are to be construed
using their broadest reasonable meaning unless they are used in a
context that requires a different interpretation.
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